Spiral Object Recognition on Clusters
نویسندگان
چکیده
Object matching has many potential applications in industry, defense and medical science. Most matching methods introduced in recent years are based on the invariant representations. Main invariants applied in computer vision are algebraic, differential invariants and integral invariants. Our approach in this paper uses an affine integral invariant within a Spiral Architecture. The invariant representation is based on the extracted object contour. The parameter to be used for parameterizing an object contour is derived from the enclosed area. The Spiral Architecture posseses powerful computation features that are pertinent to the vision process. We present a parallel algorithm for object recognition on clusters. Image partitioning based on Spiral Architecture provides well-balanced load and absolutely uniform sub-images. The cluster-based object recognition greatly inC1'eases computation speed.
منابع مشابه
Urban Vegetation Recognition Based on the Decision Level Fusion of Hyperspectral and Lidar Data
Introduction: Information about vegetation cover and their health has always been interesting to ecologists due to its importance in terms of habitat, energy production and other important characteristics of plants on the earth planet. Nowadays, developments in remote sensing technologies caused more remotely sensed data accessible to researchers. The combination of these data improves the obje...
متن کاملObject Recognition based on Local Steering Kernel and SVM
The proposed method is to recognize objects based on application of Local Steering Kernels (LSK) as Descriptors to the image patches. In order to represent the local properties of the images, patch is to be extracted where the variations occur in an image. To find the interest point, Wavelet based Salient Point detector is used. Local Steering Kernel is then applied to the resultant pixels, in ...
متن کاملApplication of Combined Local Object Based Features and Cluster Fusion for the Behaviors Recognition and Detection of Abnormal Behaviors
In this paper, we propose a novel framework for behaviors recognition and detection of certain types of abnormal behaviors, capable of achieving high detection rates on a variety of real-life scenes. The new proposed approach here is a combination of the location based methods and the object based ones. First, a novel approach is formulated to use optical flow and binary motion video as the loc...
متن کاملThe protective effect of hesperetin and nano-hesperetin on object recognition memory in animal model of Alzheimer
Background and objectives: Hesperetin (Hst), aglycone form of hesperidin, is reported to have antioxidant, anti-inflammatory and neuroprotective activities. On the other hand, the latest nanoparticle technology can help to improve the bioavailability of Hst, which is affected by the final particle size and stability. Alzheimer’s disease is a neurodegenerative disease, character...
متن کاملTomographic reconstruction of multiple in-line holograms for multiple scattering in low energy electron holography
We generate simulated holograms for low energy electron point source (LEEPS) microscopy. For a given object (atomic cluster) we construct a number of different holograms by varying the position or the orientation of the object relative to the screen. We then compare the three-dimensional structures of the reconstructions obtained from these holograms using methods developed and reported in prev...
متن کامل